Courses
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Fundamentals of Reinforcement Learning
The foundations of reinforcement learning, from the University of Alberta and the Alberta Machine Intelligence Institute (Amii).
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AI-Powered Software and System Design
Using generative AI for software architecture, databases and system design, taught by Laurence Moroney.
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Generative AI for Software Development
A three-course professional certificate from DeepLearning.AI on using LLMs throughout software development, from writing code to system design.
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Team Software Engineering with AI
Using generative AI for testing, documentation and dependency management in a team, taught by Laurence Moroney.
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Generative AI with Large Language Models
How LLMs work and how to fine-tune, align and deploy them, from DeepLearning.AI and Amazon Web Services.
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Responsible AI: Applying AI Principles with Google Cloud
How Google Cloud puts its AI principles into practice, and how to apply responsible AI in an organization.
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Introduction to Generative AI Learning Path
Google Cloud’s four-course introduction to generative AI, large language models and responsible AI.
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Build a Machine Learning Image Classifier with Python
A guided Coursera project: building and training an image classifier in Python.
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Deep Learning with PyTorch: Image Segmentation
A guided Coursera project: training an image segmentation model with PyTorch.
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Quantum Computing Summer School Training
Summer school at Nile University’s ITCS on air quality prediction with quantum computing and satellite data, ahead of the national competition.
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Migrating an application and data from Apache Cassandra™ to DataStax Enterprise
A Google Cloud project: moving an application and its data from Apache Cassandra to DataStax Enterprise.
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Support Vector Machines in Python, From Start to Finish
A guided Coursera project: building, tuning and evaluating a support vector machine in Python.
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Neural Networks and Deep Learning
The first course of Andrew Ng’s Deep Learning Specialization: how neural networks work and how to build and train them.
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Unsupervised Learning, Recommenders, Reinforcement Learning
Clustering, anomaly detection, recommender systems and reinforcement learning, from DeepLearning.AI and Stanford Online.
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Machine Learning Specialization
Andrew Ng’s three-course specialization from DeepLearning.AI and Stanford Online: supervised learning, advanced algorithms, and unsupervised learning, recommenders and RL.
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Advanced Learning Algorithms
Neural networks, decision trees and practical advice for machine learning, from DeepLearning.AI and Stanford Online.
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Supervised Machine Learning: Regression and Classification
Linear and logistic regression and the foundations of machine learning, from DeepLearning.AI and Stanford Online.